Merge branch 'main' into please_dont_modify_this_branch_unless_you_ar…

…e_just_merging_with_main_

.github/workflows/docs.yml

@@ -57,7 +57,7 @@ jobs:
         sed -i -e 's/-j auto/-j 1/' Makefile
         make html
 
-        # Below is an imperfect way for us to add "try on collab" links to all of our gallery examples.
+        # Below is an imperfect way for us to add "try on Colab" links to all of our gallery examples.
         # sphinx-gallery will convert all gallery examples to .ipynb notebooks and stores them in
         # build/html/_downloads/<some_hash>/<example_name>.ipynb
         # We copy all those ipynb files in a more convenient folder so that we can more easily link to them.

benchmarks/encoding.py

@@ -0,0 +1,67 @@
+import os
+import platform
+import statistics
+
+import torch
+import torch.utils.benchmark as benchmark
+import torchvision
+
+
+def print_machine_specs():
+    print("Processor:", platform.processor())
+    print("Platform:", platform.platform())
+    print("Logical CPUs:", os.cpu_count())
+    print(f"\nCUDA device: {torch.cuda.get_device_name()}")
+    print(f"Total Memory: {torch.cuda.get_device_properties(0).total_memory / 1e9:.2f} GB")
+
+
+def get_data():
+    transform = torchvision.transforms.Compose(
+        [
+            torchvision.transforms.PILToTensor(),
+        ]
+    )
+    path = os.path.join(os.getcwd(), "data")
+    testset = torchvision.datasets.Places365(
+        root="./data", download=not os.path.exists(path), transform=transform, split="val"
+    )
+    testloader = torch.utils.data.DataLoader(
+        testset, batch_size=1000, shuffle=False, num_workers=1, collate_fn=lambda batch: [r[0] for r in batch]
+    )
+    return next(iter(testloader))
+
+
+def run_benchmark(batch):
+    results = []
+    for device in ["cpu", "cuda"]:
+        batch_device = [t.to(device=device) for t in batch]
+        for size in [1, 100, 1000]:
+            for num_threads in [1, 12, 24]:
+                for stmt, strat in zip(
+                    [
+                        "[torchvision.io.encode_jpeg(img) for img in batch_input]",
+                        "torchvision.io.encode_jpeg(batch_input)",
+                    ],
+                    ["unfused", "fused"],
+                ):
+                    batch_input = batch_device[:size]
+                    t = benchmark.Timer(
+                        stmt=stmt,
+                        setup="import torchvision",
+                        globals={"batch_input": batch_input},
+                        label="Image Encoding",
+                        sub_label=f"{device.upper()} ({strat}): {stmt}",
+                        description=f"{size} images",
+                        num_threads=num_threads,
+                    )
+                    results.append(t.blocked_autorange())
+    compare = benchmark.Compare(results)
+    compare.print()
+
+
+if __name__ == "__main__":
+    print_machine_specs()
+    batch = get_data()
+    mean_h, mean_w = statistics.mean(t.shape[-2] for t in batch), statistics.mean(t.shape[-1] for t in batch)
+    print(f"\nMean image size: {int(mean_h)}x{int(mean_w)}")
+    run_benchmark(batch)

docs/source/conf.py

@@ -59,7 +59,7 @@
 # We override sphinx-gallery's example header to prevent sphinx-gallery from
 # creating a note at the top of the renderred notebook.
 # https://github.com/sphinx-gallery/sphinx-gallery/blob/451ccba1007cc523f39cbcc960ebc21ca39f7b75/sphinx_gallery/gen_rst.py#L1267-L1271
-# This is because we also want to add a link to google collab, so we write our own note in each example.
+# This is because we also want to add a link to google Colab, so we write our own note in each example.
 from sphinx_gallery import gen_rst
 
 gen_rst.EXAMPLE_HEADER = """

gallery/others/plot_optical_flow.py

@@ -4,7 +4,7 @@
 =====================================================
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_optical_flow.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_optical_flow.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_others_plot_optical_flow.py>` to download the full example code.
 
 Optical flow is the task of predicting movement between two images, usually two

gallery/others/plot_repurposing_annotations.py

@@ -4,7 +4,7 @@
 =====================================
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_repurposing_annotations.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_repurposing_annotations.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_others_plot_repurposing_annotations.py>` to download the full example code.
 
 The following example illustrates the operations available
@@ -149,8 +149,8 @@ def show(imgs):
 model = fasterrcnn_resnet50_fpn(weights=weights, progress=False)
 print(img.size())
 
-tranforms = weights.transforms()
-img = tranforms(img)
+transforms = weights.transforms()
+img = transforms(img)
 target = {}
 target["boxes"] = boxes
 target["labels"] = labels = torch.ones((masks.size(0),), dtype=torch.int64)

gallery/others/plot_scripted_tensor_transforms.py

@@ -4,7 +4,7 @@
 ===================
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_scripted_tensor_transforms.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_scripted_tensor_transforms.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_others_plot_scripted_tensor_transforms.py>` to download the full example code.
 
 This example illustrates `torchscript
@@ -26,7 +26,7 @@
 plt.rcParams["savefig.bbox"] = 'tight'
 torch.manual_seed(1)
 
-# If you're trying to run that on collab, you can download the assets and the
+# If you're trying to run that on Colab, you can download the assets and the
 # helpers from https://github.com/pytorch/vision/tree/main/gallery/
 import sys
 sys.path += ["../transforms"]

gallery/others/plot_video_api.py

@@ -4,7 +4,7 @@
 =========
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_video_api.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_video_api.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_others_plot_video_api.py>` to download the full example code.
 
 This example illustrates some of the APIs that torchvision offers for

gallery/others/plot_visualization_utils.py

@@ -4,7 +4,7 @@
 =======================
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_visualization_utils.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_visualization_utils.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_others_plot_visualization_utils.py>` to download the full example code.
 
 This example illustrates some of the utilities that torchvision offers for

gallery/transforms/plot_custom_transforms.py

@@ -4,7 +4,7 @@
 ===================================
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_custom_transforms.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_custom_transforms.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_transforms_plot_custom_transforms.py>` to download the full example code.
 
 This guide explains how to write transforms that are compatible with the

gallery/transforms/plot_custom_tv_tensors.py

@@ -4,7 +4,7 @@
 ====================================
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_custom_tv_tensors.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_custom_tv_tensors.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_transforms_plot_custom_tv_tensors.py>` to download the full example code.
 
 This guide is intended for advanced users and downstream library maintainers. We explain how to

gallery/transforms/plot_cutmix_mixup.py

@@ -5,7 +5,7 @@
 ===========================
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_cutmix_mixup.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_cutmix_mixup.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_transforms_plot_cutmix_mixup.py>` to download the full example code.
 
 :class:`~torchvision.transforms.v2.CutMix` and

gallery/transforms/plot_transforms_e2e.py

@@ -4,7 +4,7 @@
 ===============================================================
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_transforms_e2e.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_transforms_e2e.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_transforms_plot_transforms_e2e.py>` to download the full example code.
 
 Object detection and segmentation tasks are natively supported:
@@ -30,7 +30,7 @@
 
 # This loads fake data for illustration purposes of this example. In practice, you'll have
 # to replace this with the proper data.
-# If you're trying to run that on collab, you can download the assets and the
+# If you're trying to run that on Colab, you can download the assets and the
 # helpers from https://github.com/pytorch/vision/tree/main/gallery/
 ROOT = pathlib.Path("../assets") / "coco"
 IMAGES_PATH = str(ROOT / "images")

gallery/transforms/plot_transforms_getting_started.py

@@ -4,7 +4,7 @@
 ==================================
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_transforms_getting_started.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_transforms_getting_started.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_transforms_plot_transforms_getting_started.py>` to download the full example code.
 
 This example illustrates all of what you need to know to get started with the
@@ -25,7 +25,7 @@
 
 torch.manual_seed(1)
 
-# If you're trying to run that on collab, you can download the assets and the
+# If you're trying to run that on Colab, you can download the assets and the
 # helpers from https://github.com/pytorch/vision/tree/main/gallery/
 from helpers import plot
 img = read_image(str(Path('../assets') / 'astronaut.jpg'))

gallery/transforms/plot_transforms_illustrations.py

@@ -4,7 +4,7 @@
 ==========================
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_transforms_illustrations.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_transforms_illustrations.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_transforms_plot_transforms_illustrations.py>` to download the full example code.
 
 This example illustrates some of the various transforms available in :ref:`the
@@ -27,7 +27,7 @@
 # properly show that the image can be both transformed and *not* transformed!
 torch.manual_seed(0)
 
-# If you're trying to run that on collab, you can download the assets and the
+# If you're trying to run that on Colab, you can download the assets and the
 # helpers from https://github.com/pytorch/vision/tree/main/gallery/
 from helpers import plot
 orig_img = Image.open(Path('../assets') / 'astronaut.jpg')

gallery/transforms/plot_tv_tensors.py

@@ -4,7 +4,7 @@
 =============
 
 .. note::
-    Try on `collab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_tv_tensors.ipynb>`_
+    Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_tv_tensors.ipynb>`_
     or :ref:`go to the end <sphx_glr_download_auto_examples_transforms_plot_tv_tensors.py>` to download the full example code.